Abstract 3497: Identifying pre-clinical predictive biomarkers for the PARP inhibitor olaparib

Background: Early results from Phase II trials have shown that treatment with the PARP inhibitor olaparib (AZD2281, KU-0059436) can induce tumour specific synthetic lethality in patients with BRCA-mutated breast and ovarian cancer, with little effect on normal tissues. Pre-clinical studies have indicated that sensitivity can also result from other perturbations affecting homologous recombination (HR), suggesting broader patient populations may benefit from this drug. We aimed to generate pre-clinical hypotheses as to the key biological mechanisms regulating response to this drug; and identify associated biomarkers by which responding patient subsets could be stratified. Methods: A panel of 95 cell lines representing breast, ovarian, colorectal, lung, head & neck and pancreatic cancers was tested for sensitivity to olaparib using 2D-clonogenic survival assays. Baseline (untreated) gene expression profiles (Affymetrix U133A Plus2) were determined for each cell line, alongside protein expression and mutational status of core HR genes. Dynamic pathway gene expression signatures were collated from the literature, and additional signatures generated using RNAi against core HR components. Statistical and bioinformatic approaches were then applied to prioritise correlated networks of genes displaying consistent pathway overlay and predictive of response in cell line subsets. Results: 30 cell lines were highly sensitive to olaparib treatment (IC50 4 µM). Deleterious mutations in BRCA1 or BRCA2 genes were associated with only a small subset of highly sensitive cell lines, highlighting the presence of other factors able to modulate olaparib responsiveness. Transcriptome analysis revealed DNA repair and proliferation associated genes to be most consistently correlated with olaparib response. Based on these results, a candidate predictive baseline gene expression profile was established. Conclusions: By profiling a large panel of cell lines we have determined that factors in addition to BRCA mutation can be linked with olaparib sensitivity. A list of candidate gene transcripts predictive of in vitro sensitivity to olaparib were identified which may have utility as predictive biomarkers in the clinic. Although primarily linked to mechanisms expected to influence response (DNA repair, cell-cycle checkpoints and proliferation), novel roles were suggested for other pathways such as Aurora A kinase signalling. Analyses also highlighted th